Yes but consider for instance a one-way ANOVA with random effect :  lmer( y ~ (1 | group) )

Then the marginal distribution of the vector  y  in each group is an exchangeable normal distribution whose correlation is the ratio of the between variance over the total variance. This correlation is then restricted to be positive. The NOBOUND option in SAS PROC MIXED allows a negative estimate of this correlation. 

Of course here this is a simple example and we can model the general exchangeable Gaussian distribution with lme(), but for other examples it is not so easy. 

When a variance estimate is zero, the NOBOUND option is useful to assess if this is "really zero" or if it is rather a negative estimate, thereby indicating that the model is not correct and that we should use a model for which this variance is actually a possibly negative covariance.

Checking if there are negative variance estimates with the NOBOUND option can also help to detect outliers. 

SL


________________________________
 De : Douglas Bates <bates@stat.wisc.edu>
À : Callie Baird <calliebaird@gmail.com> 
Cc : R-mixed models mailing list <r-sig-mixed-models@r-project.org> 
Envoyé le : Mardi 4 juin 2013 17h46
Objet : Re: [R-sig-ME] Negative Variance


On Tue, Jun 4, 2013 at 9:01 AM, Callie Baird <calliebaird@gmail.com> wrote:

> I am trying to fit multilevel models, allowing negative variance estimates.
>  Is there a way to allow negative variance estimates as in nobound in SAS?
>

No, and I, for one, am not likely to add it.  See

install.packages("fortunes")
library(fortunes)
fortune("impossibility")

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